{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 卷积神经网络\n",
    "本章的主题是**卷积神经网络**(Convolutional Netural Network, CNN)。\n",
    "\n",
    "CNN 被用于图像识别、语音识别等各种场合，在图像识别的比赛中，基于深度学习的方法几乎都以 CNN 为基础。"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 整体结构\n",
    "\n",
    "CNN 中新出现了**卷积层(Convolution层)** 和 **池化层(Pooling层)**。\n",
    "\n",
    "之前介绍的神经网络中，相邻层的所有神经元之间都有连接，这称为**全连接**(fully-connected)。\n",
    "\n",
    "一个5层的使用了 Affine 层的全连接的神经网络可以通过下图的网络结构来实现。全连接的神经网络中，Affine 层后面跟着激活函数 ReLU 层(或者Sigmoid层)。这里堆叠了4层“Affine-ReLU”组合，然后第5层是 Affine 层，最后由 Softmax 层输出最终结果(概率)。\n",
    "\n",
    "![image.png](attachment:image.png)\n",
    "\n",
    "那么，CNN 会是什么样的结构呢，如下图。\n",
    "![image.png](attachment:image.png)\n",
    "\n",
    "如图所示，CNN 中新增了 Convolution 层 和 Pooling 层。CNN 层的连接顺序是“Convolution - ReLU - (Pooling)”(Pooling 层有时候会被省略)。"
   ]
  }
 ],
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   "language": "python",
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    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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